prompt-evaluation

Evaluate prompt quality against clarity, specificity, context, constraints, and examples.

Updated Mar 10, 2026

Search Tags:#prompt engineering #prompt optimization #ai evaluation #prompt quality #chain of verification

Ready to run

npx skills add https://github.com/Ankh-Studio/copilot-enterprise-eval-plugin --skill prompt-evaluation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prompt-evaluation
Source: https://github.com/Ankh-Studio/copilot-enterprise-eval-plugin/tree/main/.windsurf/skills/prompt-evaluation
Command: npx skills add https://github.com/Ankh-Studio/copilot-enterprise-eval-plugin --skill prompt-evaluation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @chain-of-verification/core, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of creating clear, effective, and reliable prompts for AI interactions by providing a structured evaluation process.

Core Features & Use Cases

Prompt Quality Assessment: Evaluates prompts based on predefined criteria like clarity, specificity, context, constraints, and examples.
Chain-of-Verification: Employs a self-critique mechanism to identify potential issues and suggest improvements.
Use Case: A developer struggling to get consistent results from an AI assistant can use this Skill to analyze and refine their prompts, leading to more predictable and accurate AI outputs.

Quick Start

Use the prompt-evaluation skill to analyze the prompt in the file '.github/prompts/api-design.prompt.md'.

Frequently Asked Questions about prompt-evaluation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I evaluate prompt quality and effectiveness for AI interactions?▼

To evaluate prompt quality, analyze the prompt against criteria including clarity, specificity, context, constraints, and examples, then apply a self-critique mechanism to score and identify potential issues for improvement.

What is the Chain-of-Verification methodology for prompt optimization?▼

Chain-of-Verification is a self-critique mechanism that evaluates prompt quality by identifying potential issues and suggesting improvements, resulting in more predictable and accurate AI outputs.

How do I refine prompts to get consistent results from an AI assistant?▼

Refine prompts by evaluating them against predefined criteria like clarity and constraints, followed by a self-critique process that scores the prompt and highlights areas needing improvement for better AI performance.

Can I use this prompt evaluation skill to analyze prompt files in my repository?▼

Yes, you can evaluate prompt files by specifying the file path, such as analyzing the prompt in the file '.github/prompts/api-design.prompt.md' to assess its quality and effectiveness.

Does prompt evaluation require any specific dependencies?▼

Yes, prompt evaluation requires the @chain-of-verification/core dependency to execute its self-critique mechanism and accurately score prompt quality across multiple criteria.

When should I use a structured prompt evaluation process instead of manual tweaking?▼

Use structured prompt evaluation when struggling to get consistent AI results, as it provides a systematic analysis of clarity, specificity, context, constraints, and examples rather than relying on manual trial and error.